Investigate the potential of satellite altimeters in estimating surface soil moisture in semi-arid areas

Document Type : Research Article

Authors

1 Department of Geodesy Engineering, South Tehran, Islamic Azad University, Tehran, Iran.

2 Department of Geodesy, Faculty of Geodesy and Geomatics Engineering, K. N. Toosi University of Technology, Tehran, Iran.

Abstract

Surface soil moisture is an important variable in the climate system, controlling the exchange of water, energy and carbon, between the Earth's surface and the atmosphere. Also, the quantification of surface soil moisture is necessary for the simulation of climate change, the prediction of floods and droughts and the optimal irrigation of agricultural land. Satellite altimeters are often used to monitor water levels (ocean and inland waters such as lakes, rivers and dams) and the dynamics of ice sheets. However, due to the influence of surface roughness on the return waveforms captured by altimeters, they can also be used to estimate surface features such as surface soil moisture. Against this backdrop, the main objective of this study is to investigate the potential of conventional altimeters (Low Resolution Mode (LRM) satellite altimeters such as Jason series satellites, Envisat, Saral and...) and new generation altimeters (synthetic aperture radar (SAR) satellite altimeters such as Cryosat-2, Sentinel-3 and Sentinel-6) in the estimation of surface soil moisture in the semi-arid region of Spain over the period from 2016 to 2023. To achieve this goal, level 2 (L2) data from the SRAL altimeter sensor of Sentinel-3A satellite along the pass of 644 and geophysical data record (GDR) from the Poseidon-3B altimeter sensor of Jason-3 satellite along the pass of 213 were used. In addition to the different acquisition geometry of these two altimetry satellites, the effectiveness of the re-tracking algorithms used in them in estimating soil surface moisture, was also questioned in this study. The relationships between the observed backscattering coefficients derived from 4 re-tracking algorithms (re-tracker: Ocean re-tracker, OCOG re-tracker, Sea-ice re-tracker and Ice-sheet re-tracker) in the L2 data of the Sentinel-3A satellite additionally 3 re-tracking algorithms (re-tracker: MLE-4 re-tracker, MLE-3 re-tracker and Ice re-tracker) in the GDR data of the Jason-3 satellite and the surface soil moisture obtained from ground stations (the closest ground station to the satellite pass was selected) were investigated. The results of the analysis, demonstrate a strong linear relationship between the scattering coefficients derived from the satellite data and the corresponding soil moisture measurements obtained from ground stations along the coverage of the two satellites. The best results (the highest correlation coefficient) for the Sentinel-3A and Jason-3 satellites were achieved with the Ocean Re-tracker (with a correlation coefficient of 0.75), and the Ice Re-tracker (with a correlation coefficient of 0.7), respectively. MLE-3 re-tracker in Jason-3 Satellite has also obtained a result almost similar to ICE re-tracker in one of the ground stations. While the results express the high performance of the Sentinel-3A and Jason-3 satellites in estimating surface soil moisture, they show the superiority of synthetic aperture radar altimeters over the conventional altimeters in estimating surface soil moisture in the area studied.

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References

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Journal of the Earth and Space Physics
Volume 50, Issue 3
online publication date: 5 Oct 2024
October 2024
Pages 637-654

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